An efficient variable selection-based Kriging model method for the reliability analysis of slopes with spatially variable soils

Jiayi Ding, Jianfang Zhou and Wei Cai

Reliability Engineering and System Safety, 2023, vol. 235, issue C

Abstract: The random finite element method (RFEM) is an efficient tool to demonstrate the spatial variability of soil properties during reliability analysis of slopes, but it requires remarkable model evaluations and computational efforts. In this paper, an efficient variable selection-based Kriging model method is proposed to approximate the finite element analysis model in reliability analysis of slopes. The variable selection technique successfully remedies the “curse of dimensionality†within Kriging model induced by the numerous random variables in random field discretization. The implementation procedure of this method for the reliability analysis of slopes is introduced in detail. Two typical examples of soil slopes, as well as a real complex slope are subsequently analyzed to illustrate the validity of the proposed method. The results show that the local loss of variability of random field due to the variable selection method has little impact on the safety factor of slopes. The proposed method can significantly reduce the number of finite element analysis and obtain accurate results in reliability analysis of slopes considering the spatial variability of soil properties.

Keywords: Random field; Variable selection; Kriging model; Active learning; Reliability; Slope stability (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (6)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:235:y:2023:i:c:s0951832023001497

DOI: 10.1016/j.ress.2023.109234

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